RESUMO
BACKGROUND: Since most people in low-income countries do not have access to reliable laboratory services, early diagnosis of life-threatening diseases like COVID-19 remains challenging. Facilitating real-time assessment of the health status in a given population, mobile health (mHealth)-supported syndrome surveillance might help identify disease conditions earlier and save lives cost-effectively. OBJECTIVE: This study aimed to evaluate the potential use of mHealth-supported active syndrome surveillance for COVID-19 early case finding in Addis Ababa, Ethiopia. METHODS: A comparative cross-sectional study was conducted among adults randomly selected from the Ethio telecom list of mobile phone numbers. Participants underwent a comprehensive phone interview for COVID-19 syndromic assessments, and their symptoms were scored and interpreted based on national guidelines. Participants who exhibited COVID-19 syndromes were advised to have COVID-19 diagnostic testing at nearby health care facilities and seek treatment accordingly. Participants were asked about their test results, and these were cross-checked against the actual facility-based data. Estimates of COVID-19 detection by mHealth-supported syndromic assessments and facility-based tests were compared using Cohen Kappa (κ), the receiver operating characteristic curve, sensitivity, and specificity analysis. RESULTS: A total of 2741 adults (n=1476, 53.8% men and n=1265, 46.2% women) were interviewed through the mHealth platform during the period from December 2021 to February 2022. Among them, 1371 (50%) had COVID-19 symptoms at least once and underwent facility-based COVID-19 diagnostic testing as self-reported, with 884 (64.5%) confirmed cases recorded in facility-based registries. The syndrome assessment model had an optimal likelihood cut-off point sensitivity of 46% (95% CI 38.4-54.6) and specificity of 98% (95% CI 96.7-98.9). The area under the receiver operating characteristic curve was 0.87 (95% CI 0.83-0.91). The level of agreement between the mHealth-supported syndrome assessment and the COVID-19 test results was moderate (κ=0.54, 95% CI 0.46-0.60). CONCLUSIONS: In this study, the level of agreement between the mHealth-supported syndromic assessment and the actual laboratory-confirmed results for COVID-19 was found to be reasonable, at 89%. The mHealth-supported syndromic assessment of COVID-19 represents a potential alternative method to the standard laboratory-based confirmatory diagnosis, enabling the early detection of COVID-19 cases in hard-to-reach communities, and informing patients about self-care and disease management in a cost-effective manner. These findings can guide future research efforts in developing and integrating digital health into continuous active surveillance of emerging infectious diseases.
RESUMO
Background: Tuberculosis (TB) prevalence is increasing among women of reproductive age (WRA) in sub-Saharan Africa, yet undiagnosed and untreated cases remain rather high with serious health and socio-economic consequences. We aimed to assess the prevalence and predictors of TB in WRA seeking health care for acute respiratory symptoms. Methods: We consecutively enrolled outpatient WRA with acute respiratory symptoms seeking care at four healthcare facilities in Ethiopia between July 2019 and December 2020. Data on sociodemographic characteristics and clinical information were collected using a structured questionnaire administered by trained nurses. Posteroanterior chest X-ray was performed in non-pregnant WRA and interpreted independently by two radiologists. Sputum samples were collected from all patients and tested for pulmonary TB using Xpert MTB/RIF and/or smear microscopy. Predictors of bacteriologically confirmed TB cases were determined using binary logistic regression, with clinically relevant variables included in the final Firth's multivariate-penalized logistic regression model. Results: We enrolled 577 participants, of whom 95 (16%) were pregnant, 67 (12%) were living with HIV, 512 (89%) had cough of less than 2 weeks, and 56 (12%) had chest-x-ray findings suggestive of TB. The Overall prevalence of TB was 3% (95% CI: 1.8%-4.7%) with no significant difference observed between patient groups categorized by duration of cough or HIV serostatus (P-value = 0.9999). In multivariable analysis, TB-suggestive CXR abnormality (AOR 18.83 [95% CI, 6.20-57.18]) and history of weight loss (AOR 3.91 [95% CI, 1.25-12.29]) were associated with bacteriologically-confirmed TB cases. Conclusions: We found a high TB prevalence among low-risk women of reproductive age with acute respiratory symptoms. Routine CXR may improve early case detection and thereby TB treatment outcomes.
RESUMO
Background: Children share 12% of the global 10 million people infected with tuberculosis (TB) each year. Closing case detection gap in children remains difficult, with 56% of all children and 65% under-five with TB missed each year. We aimed to assess the patterns of childhood TB diagnosis and underlying determinants in Ethiopia when different TB diagnostic platforms are applied. Methods: A multi-site, cross-sectional study was carried out in Ethiopia as part of the larger EXIT-TB study - evidence-based multiple focused integrated intensified TB screening package. Outpatient children aged ≤ 15 with cough of any duration seeking care at four healthcare facilities in Ethiopia were enrolled consecutively. Participants underwent sputum Xpert MTB/RIF and/or smear microscopy and posteroanterior chest X-ray (CXR), and their clinical and sociodemographic data were captured using a structured questionnaire. Data were analyzed using Stata version 23. Multiple regression model was computed to determine the factors that influence TB case detection, with a 95% confidence interval (CI) and p < 0.05 taken as statistically significant. Results: A total of 438 children were enrolled. Of these, 399 had CXR examination of which 55 (13.8%) were suggestive of TB, 270 had Xpert MTB/RIF testing of which 32 (11.9%) were positive, and AFB smear microscopy was done for 51 children of which 2 (3.9%) were positive. Febrile children were more likely to be diagnosed with pulmonary TB than those without fever [aPR = 1.3, 95% CI (1.1-1.4)], and those with a TB contact history were more likely to be diagnosed with pulmonary TB than those with no such contacts [aPR = 1.2, 95% CI (1.1-1.3)]. Children from rural residences were more likely to be diagnosed with TB than those from urban residences [aPR = 1.3, 95% CI (1.1-1.5)]. Conclusion: The findings showed that clinical diagnosis remains an important method of TB diagnosis in children and the preferred choice to avert underdiagnosis. A more sensitive TB diagnostic method for children was symptom screening, followed by CXR and Xpert MTB/RIF assay or smear microscopy. Hence, an algorithm that combines clinical, CXR, and microbiological confirmatory tests can improve the rate of pulmonary TB diagnosis in children till more accurate and cost-effective diagnostic tools are accessible. Fever, weight loss, and TB contact history are highly associated with TB positivity rates in children.